Integration of Distributed Manufacturing Nodes in Smart Factory

2018 ◽  
pp. 424-435
Author(s):  
Miha Pipan ◽  
Jernej Protner ◽  
Niko Herakovič
Keyword(s):  
Smart Factory ◽  
Distributed Manufacturing

scholarly journals Performance Analysis of SDN-based Global Mobility Support Scheme in Smart Factory Networks

2019 ◽  
Vol 155 ◽  
pp. 145-152
Author(s):  
Jaehyeong Lee ◽  
Changyong Um ◽  
Guejong Jo ◽  
Dogun Park ◽  
Jongpil Jeong
Keyword(s):  
Performance Analysis ◽  
Smart Factory ◽  
Mobility Support ◽  
Global Mobility

A Smart Factory Setup based on the RoboCup Logistics League

2020 ◽  
Author(s):  
Niklas Sebastian Eltester ◽  
Alexander Ferrein ◽  
Stefan Schiffer
Keyword(s):  
Smart Factory

Von Science-Fiction zur Realität: Robotik in der Smart Factory

Digitale Welt ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 74-75
Author(s):  
Robert Frodl
Keyword(s):  
Science Fiction ◽  
Smart Factory

scholarly journals UWB Localization in a Smart Factory: Augmentation Methods and Experimental Assessment

2021 ◽  
pp. 1-1
Author(s):  
Luca Barbieri ◽  
Mattia Brambilla ◽  
Andrea Trabattoni ◽  
Stefano Mervic ◽  
Monica Nicoli
Keyword(s):  
Smart Factory ◽  
Experimental Assessment

Implementation of MQTT protocol based network architecture for smart factory

2021 ◽  
pp. 095440542110144
Author(s):  
Chia-Shin Yeh ◽  
Shang-Liang Chen ◽  
I-Ching Li
Keyword(s):  
Machine Tool ◽  
Gesture Recognition ◽  
Manufacturing Process ◽  
Network Architecture ◽  
Information Management System ◽  
Edge Computing ◽  
Smart Factory ◽  
Smart Manufacturing ◽  
Industrial Iot ◽  
Computing Module

The core concept of smart manufacturing is based on digitization to construct intelligent production and management in the manufacturing process. By digitizing the production process and connecting all levels from product design to service, the purpose of improving manufacturing efficiency, reducing production cost, enhancing product quality, and optimizing user experience can be achieved. To digitize the manufacturing process, IoT technology will have to be introduced into the manufacturing process to collect and analyze process information. However, one of the most important problems in building the industrial IoT (IIoT) environment is that different industrial network protocols are used for different equipment in factories. Therefore, the information in the manufacturing process may not be easily exchanged and obtained. To solve the above problem, a smart factory network architecture based on MQTT (MQ Telemetry Transport), IoT communication protocol, is proposed in this study, to construct a heterogeneous interface communication bridge between the machine tool, embedded device Raspberry Pi, and website. Finally, the system architecture is implemented and imported into the factory, and a smart manufacturing information management system is developed. The edge computing module is set up beside a three-axis machine tool, and a human-machine interface is built for the user controlling and monitoring. Users can also monitor the system through the dynamically updating website at any time and any place. The function of real-time gesture recognition based on image technology is developed and built on the edge computing module. The gesture recognition results can be transmitted to the machine controller through MQTT, and the machine will execute the corresponding action according to different gestures to achieve human-robot collaboration. The MQTT transmission architecture developed here is validated by the given edge computing application. It can serve as the basis for the construction of the IIoT environment, assist the traditional manufacturing industry to prepare for digitization, and accelerate the practice of smart manufacturing.

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